Relevant bibliographies by topics / Biosensor

Academic literature on the topic 'Biosensor'

Author: Grafiati
Published: 4 June 2021
Last updated: 7 July 2024

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Journal articles on the topic "Biosensor"

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Rafat, Neda, Paul Satoh, and Robert Mark Worden. "Electrochemical Biosensor for Markers of Neurological Esterase Inhibition." Biosensors 11, no. 11 (November 16, 2021): 459. http://dx.doi.org/10.3390/bios11110459.

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A novel, integrated experimental and modeling framework was applied to an inhibition-based bi-enzyme (IBE) electrochemical biosensor to detect acetylcholinesterase (AChE) inhibitors that may trigger neurological diseases. The biosensor was fabricated by co-immobilizing AChE and tyrosinase (Tyr) on the gold working electrode of a screen-printed electrode (SPE) array. The reaction chemistry included a redox-recycle amplification mechanism to improve the biosensor’s current output and sensitivity. A mechanistic mathematical model of the biosensor was used to simulate key diffusion and reaction steps, including diffusion of AChE’s reactant (phenylacetate) and inhibitor, the reaction kinetics of the two enzymes, and electrochemical reaction kinetics at the SPE’s working electrode. The model was validated by showing that it could reproduce a steady-state biosensor current as a function of the inhibitor (PMSF) concentration and unsteady-state dynamics of the biosensor current following the addition of a reactant (phenylacetate) and inhibitor phenylmethylsulfonylfluoride). The model’s utility for characterizing and optimizing biosensor performance was then demonstrated. It was used to calculate the sensitivity of the biosensor’s current output and the redox-recycle amplification factor as a function of experimental variables. It was used to calculate dimensionless Damkohler numbers and current-control coefficients that indicated the degree to which individual diffusion and reaction steps limited the biosensor’s output current. Finally, the model’s utility in designing IBE biosensors and operating conditions that achieve specific performance criteria was discussed.
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Štukovnik, Zala, Regina Fuchs-Godec, and Urban Bren. "Nanomaterials and Their Recent Applications in Impedimetric Biosensing." Biosensors 13, no. 10 (September 22, 2023): 899. http://dx.doi.org/10.3390/bios13100899.

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Impedimetric biosensors measure changes in the electrical impedance due to a biochemical process, typically the binding of a biomolecule to a bioreceptor on the sensor surface. Nanomaterials can be employed to modify the biosensor’s surface to increase the surface area available for biorecognition events, thereby improving the sensitivity and detection limits of the biosensor. Various nanomaterials, such as carbon nanotubes, carbon nanofibers, quantum dots, metal nanoparticles, and graphene oxide nanoparticles, have been investigated for impedimetric biosensors. These nanomaterials have yielded promising results in improving sensitivity, selectivity, and overall biosensor performance. Hence, they offer a wide range of possibilities for developing advanced biosensing platforms that can be employed in various fields, including healthcare, environmental monitoring, and food safety. This review focuses on the recent developments in nanoparticle-functionalized electrochemical-impedimetric biosensors.
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Turdean, Graziella L. "Design and Development of Biosensors for the Detection of Heavy Metal Toxicity." International Journal of Electrochemistry 2011 (2011): 1–15. http://dx.doi.org/10.4061/2011/343125.

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Many compounds (including heavy metals, HMs) used in different fields of industry and/or agriculture act as inhibitors of enzymes, which, as consequence, are unable to bind the substrate. Even if it is not so sensitive, the method for detecting heavy metal traces using biosensors has a dynamic trend and is largely applied for improving the “life quality”, because of biosensor's sensitivity, selectivity, and simplicity. In the last years, they also become more and more a synergetic combination between biotechnology and microelectronics. Dedicated biosensors were developed for offline and online analysis, and also, their extent and diversity could be called a real “biosensor revolution”. A panel of examples of biosensors: enzyme-, DNA-, imuno-, whole-cell-based biosensors were systematised depending on the reaction type, transduction signal, or analytical performances. The mechanism of enzyme-based biosensor and the kinetic of detection process are described and compared. In this context, is explainable why bioelectronics, nanotechnology, miniaturization, and bioengineering will compete for developing sensitive and selective biosensors able to determine multiple analytes simultaneously and/or integrated in wireless communications systems.
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Gilani Mohamed, Mohamed Ahmed, Ashok Vajravelu, and Nurmiza Binti Othman. "Biosensors Preliminary Concepts and Its Principles with Applications in the Engineering Perspective." International Journal of Science and Healthcare Research 6, no. 2 (May 3, 2021): 77–81. http://dx.doi.org/10.52403/ijshr.20210415.

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Biosensor is rapid detection of any infectious disease at the early stages is critical for supporting public health and ensuring effective healthcare outcomes. A timely and accurate diagnosis of a disease is necessary for an effective medical response where is biosensor takes place. The design and development of biosensors have taken a centre stage for researchers or scientists in the recent decade owing to the wide range of biosensor applications, such as health care and disease diagnosis, environmental monitoring, water and food quality monitoring, and drug delivery and lately it shown great potential for use in tissue engineering and regenerative medicine. Biosensors are ideally suited to many diagnostic and real-time detection problems due to their use of biological molecules, tissues, and cells, and their high capacity for precision and accuracy promises to continue this trend. Biosensors will become even more widespread and essential to the industrial, agricultural, scientific, and health care as biotechnology tools advance to allow additional biosensor growth. Keywords: biosensor, biosensor historical perspective, biosensor parameters, biosensor application.
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Schackart, Kenneth E., and Jeong-Yeol Yoon. "Machine Learning Enhances the Performance of Bioreceptor-Free Biosensors." Sensors 21, no. 16 (August 17, 2021): 5519. http://dx.doi.org/10.3390/s21165519.

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Since their inception, biosensors have frequently employed simple regression models to calculate analyte composition based on the biosensor’s signal magnitude. Traditionally, bioreceptors provide excellent sensitivity and specificity to the biosensor. Increasingly, however, bioreceptor-free biosensors have been developed for a wide range of applications. Without a bioreceptor, maintaining strong specificity and a low limit of detection have become the major challenge. Machine learning (ML) has been introduced to improve the performance of these biosensors, effectively replacing the bioreceptor with modeling to gain specificity. Here, we present how ML has been used to enhance the performance of these bioreceptor-free biosensors. Particularly, we discuss how ML has been used for imaging, Enose and Etongue, and surface-enhanced Raman spectroscopy (SERS) biosensors. Notably, principal component analysis (PCA) combined with support vector machine (SVM) and various artificial neural network (ANN) algorithms have shown outstanding performance in a variety of tasks. We anticipate that ML will continue to improve the performance of bioreceptor-free biosensors, especially with the prospects of sharing trained models and cloud computing for mobile computation. To facilitate this, the biosensing community would benefit from increased contributions to open-access data repositories for biosensor data.
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Newton, Adam J. H., Mark J. Wall, and Magnus J. E. Richardson. "Modeling microelectrode biosensors: free-flow calibration can substantially underestimate tissue concentrations." Journal of Neurophysiology 117, no. 3 (March 1, 2017): 937–49. http://dx.doi.org/10.1152/jn.00788.2016.

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Microelectrode amperometric biosensors are widely used to measure concentrations of analytes in solution and tissue including acetylcholine, adenosine, glucose, and glutamate. A great deal of experimental and modeling effort has been directed at quantifying the response of the biosensors themselves; however, the influence that the macroscopic tissue environment has on biosensor response has not been subjected to the same level of scrutiny. Here we identify an important issue in the way microelectrode biosensors are calibrated that is likely to have led to underestimations of analyte tissue concentrations. Concentration in tissue is typically determined by comparing the biosensor signal to that measured in free-flow calibration conditions. In a free-flow environment the concentration of the analyte at the outer surface of the biosensor can be considered constant. However, in tissue the analyte reaches the biosensor surface by diffusion through the extracellular space. Because the enzymes in the biosensor break down the analyte, a density gradient is set up resulting in a significantly lower concentration of analyte near the biosensor surface. This effect is compounded by the diminished volume fraction (porosity) and reduction in the diffusion coefficient due to obstructions (tortuosity) in tissue. We demonstrate this effect through modeling and experimentally verify our predictions in diffusive environments. NEW & NOTEWORTHY Microelectrode biosensors are typically calibrated in a free-flow environment where the concentrations at the biosensor surface are constant. However, when in tissue, the analyte reaches the biosensor via diffusion and so analyte breakdown by the biosensor results in a concentration gradient and consequently a lower concentration around the biosensor. This effect means that naive free-flow calibration will underestimate tissue concentration. We develop mathematical models to better quantify the discrepancy between the calibration and tissue environment and experimentally verify our key predictions.
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Generalov, Vladimir, Anastasia Cheremiskina, Alexander Glukhov, Victoria Grabezhova, Margarita Kruchinina, and Alexander Safatov. "Investigation of Limitations in the Detection of Antibody + Antigen Complexes Using the Silicon-on-Insulator Field-Effect Transistor Biosensor." Sensors 23, no. 17 (August 29, 2023): 7490. http://dx.doi.org/10.3390/s23177490.

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The SOI-FET biosensor (silicon-on-insulator field-effect transistor) for virus detection is a promising device in the fields of medicine, virology, biotechnology, and the environment. However, the applications of modern biosensors face numerous problems and require improvement. Some of these problems can be attributed to sensor design, while others can be attributed to technological limitations. The aim of this work is to conduct a theoretical investigation of the “antibody + antigen” complex (AB + AG) detection processes of a SOI-FET biosensor, which may also solve some of the aforementioned problems. Our investigation concentrates on the analysis of the probability of AB + AG complex detection and evaluation. Poisson probability density distribution was used to estimate the probability of the adsorption of the target molecules on the biosensor’s surface and, consequently, to obtain correct detection results. Many implicit and unexpected causes of error detection have been identified for AB + AG complexes using SOI-FET biosensors. We showed that accuracy and time of detection depend on the number of SOI-FET biosensors on a crystal.
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Miller, Corwin A., Joanne M. L. Ho, and Matthew R. Bennett. "Strategies for Improving Small-Molecule Biosensors in Bacteria." Biosensors 12, no. 2 (January 25, 2022): 64. http://dx.doi.org/10.3390/bios12020064.

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In recent years, small-molecule biosensors have become increasingly important in synthetic biology and biochemistry, with numerous new applications continuing to be developed throughout the field. For many biosensors, however, their utility is hindered by poor functionality. Here, we review the known types of mechanisms of biosensors within bacterial cells, and the types of approaches for optimizing different biosensor functional parameters. Discussed approaches for improving biosensor functionality include methods of directly engineering biosensor genes, considerations for choosing genetic reporters, approaches for tuning gene expression, and strategies for incorporating additional genetic modules.
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Theyagarajan, K., and Young-Joon Kim. "Recent Developments in the Design and Fabrication of Electrochemical Biosensors Using Functional Materials and Molecules." Biosensors 13, no. 4 (March 27, 2023): 424. http://dx.doi.org/10.3390/bios13040424.

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Electrochemical biosensors are superior technologies that are used to detect or sense biologically and environmentally significant analytes in a laboratory environment, or even in the form of portable handheld or wearable electronics. Recently, imprinted and implantable biosensors are emerging as point-of-care devices, which monitor the target analytes in a continuous environment and alert the intended users to anomalies. The stability and performance of the developed biosensor depend on the nature and properties of the electrode material or the platform on which the biosensor is constructed. Therefore, the biosensor platform plays an integral role in the effectiveness of the developed biosensor. Enormous effort has been dedicated to the rational design of the electrode material and to fabrication strategies for improving the performance of developed biosensors. Every year, in the search for multifarious electrode materials, thousands of new biosensor platforms are reported. Moreover, in order to construct an effectual biosensor, the researcher should familiarize themself with the sensible strategies behind electrode fabrication. Thus, we intend to shed light on various strategies and methodologies utilized in the design and fabrication of electrochemical biosensors that facilitate sensitive and selective detection of significant analytes. Furthermore, this review highlights the advantages of various electrode materials and the correlation between immobilized biomolecules and modified surfaces.
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Khan, Marya, Vandana Nagal, Sakeena Masrat, Talia Tuba, Nirmalya Tripathy, Mohammad K. Parvez, Mohammed S. Al-Dosari, et al. "Wide-Linear Range Cholesterol Detection Using Fe2O3 Nanoparticles Decorated ZnO Nanorods Based Electrolyte-Gated Transistor." Journal of The Electrochemical Society 169, no. 2 (February 1, 2022): 027512. http://dx.doi.org/10.1149/1945-7111/ac51f6.

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Electrolyte-gated transistor (EGT)-based biosensors are created with nanomaterials to harness the advantages of miniaturization and excellent sensing performance. A cholesterol EGT biosensor based on iron oxide (Fe2O3) nanoparticles decorated ZnO nanorods is proposed here. ZnO nanorods are directly grown on the seeded channel using a hydrothermal method, keeping in mind the stability of nanorods on the channel during biosensor measurements in an electrolyte. Most importantly, ZnO nanorods can be effectively grown and modified with Fe2O3 nanoparticles to enhance stability, surface roughness, and performance. The cholesterol oxidase (ChOx) enzyme is immobilized over Fe2O3 nanoparticles decorated ZnO nanorods for cholesterol detection. With cholesterol addition in buffer solution, the electro-oxidation of cholesterol on enzyme immobilized surface led to increased the biosensor’s current response. The cholesterol EGT biosensor detected cholesterol in wide-linear range (i.e., 0.1 to 60.0 mM) with high sensitivity (37.34 μA mM−1cm−2) compared to conventional electrochemical sensors. Furthermore, we obtained excellent selectivity, fabrication reproducibility, long-term storage stability, and practical applicability in real serum samples. The demonstrated EGT biosensor can be extended with changing enzymes or nanomaterials or hybrid nanomaterials for specific analyte detection.
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Dissertations / Theses on the topic "Biosensor"

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Nightingale, Joshua Ryan. "Optical biosensors SPARROW biosensor and photonic crystal-based fluorescence enhancement /." Morgantown, W. Va. : [West Virginia University Libraries], 2008. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=5818.

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Thesis (M.S.)--West Virginia University, 2008.
Title from document title page. Document formatted into pages; contains vi, 120 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 91-100).
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Rogerson, Jonathan G. "Biosensor technology : applications in microbial toxicology." Thesis, University of Bedfordshire, 1997. http://hdl.handle.net/10547/621817.

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This work describes the development of mediated amperometric biosensors that are able to monitor the metabolic activity of both single and mixed microbial populations, with applications in toxicity assessment and wastewater treatment plant protection. Biosensor systems have been constructed incorporating either the single-species eubacteria Escherichia coli or Pseudomonas putida, Bioseed®, or a mixture of activated sludge organisms from wastewater treatment plants, as the sensing components immobilised on disposable screen printed electrodes in stirred reaction vials. The biosensor approach is generic allowing for a wide range of microbial cell types to be employed. Appropriate bacterial species can be selected for specific sensor applications in order to confer validity and relevance to the test, hence the biosensor can be tailor-made to assess the toxicity in a particular environment and provide diagnostically valid and relevant results. The biosensors have been used to assess the toxicity of a standard toxicant and toxicant formulations and in blind testing of a range of industrial effluents, in parallel with a number of bioassays including Microtox® and activated sludge respiration inhibition. The biosensor results generally show significant correlation to the appropriate conventional toxicity tests. In this study, an activated sludge based biosensor assay was developed and used to assess the toxicity of industrial process and site effluents with the specific purpose of wastewater treatment plant protection. Data generated compared significantly with those from an activated sludge respiration inhibition test, with added advantages of rapidity, safety and ease of use.
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Ravindran, Ramasamy. "An electronic biosensing platform." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/44774.

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The objective of this research was to develop the initial constituents of a highly scalable and label-free electronic biosensing platform. Current immunoassays are becoming increasingly incapable of taking advantage of the latest advances in disease biomarker identification, hindering their utility in the potential early-stage diagnosis and treatment of many diseases. This is due primarily to their inability to simultaneously detect large numbers of biomarkers. The platform presented here - termed the electronic microplate - embodies a number of qualities necessary for clinical and laboratory relevance as a next-generation biosensing tool. Silicon nanowire (SiNW) sensors were fabricated using a purely top-down process based on those used for non-planar integrated circuits on silicon-on-insulator wafers and characterized in both dry and in biologically relevant ambients. Canonical pH measurements validated the sensing capabilities of the initial SiNW test devices. A low density SiNW array with fluidic wells constituting isolated sensing sites was fabricated using this process and used to differentiate between both cancerous and healthy cells and to capture superparamagnetic particles from solution. Through-silicon vias were then incorporated to create a high density sensor array, which was also characterized in both dry and phosphate buffered saline ambients. The result is the foundation for a platform incorporating versatile label-free detection, high sensor densities, and a separation of the sensing and electronics layers. The electronic microplate described in this work is envisioned as the heart of a next-generation biosensing platform compatible with conventional clinical and laboratory workflows and one capable of fostering the realization of personalized medicine.
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Lias, R. J. "A conductimetric biosensor." Thesis, University of Cambridge, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.373268.

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Colby, Edward Grellier. "A smart biosensor." Thesis, University of Cambridge, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.368100.

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Arnold, Peter Thomas. "A monolithic biosensor." Thesis, University of Cambridge, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.307060.

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Badescu, George Octavian. "Phytohormone biosensor development." Thesis, University of Warwick, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.487811.

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Miller, Kevin, Jeremy Williams, and James Nimlos. "PORTABLE GLUTEN BIOSENSOR." Thesis, The University of Arizona, 2009. http://hdl.handle.net/10150/192520.

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HOWARD, SHAUN CHRISTOPHER. "PHASE SEPARATION IN MIXED ORGANOSILANE MONOLAYERS: A MODEL SYSTEM FOR THE DEVELOPMENT OF NOVEL MEMBRANES." University of Cincinnati / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1123873986.

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Habermüller, Katja-Carola. "Modifizierte Polypyrrolfilme als Basis einer adaptierbaren Sensorarchitektur für reagenzlose Biosensoren." [S.l. : s.n.], 1999. http://deposit.ddb.de/cgi-bin/dokserv?idn=959536183.

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Books on the topic "Biosensor"

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Neeti, Sadana, and ScienceDirect (Online service), eds. Handbook of biosensors and biosensor kinetics. Amsterdam: Elsevier Science, 2010.

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Li, Songjun, Jagdish Singh, He Li, and Ipsita A. Banerjee, eds. Biosensor Nanomaterials. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2011. http://dx.doi.org/10.1002/9783527635160.

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service), Wiley InterScience (Online, ed. Biosensor nanomaterials. Weinheim: Wiley-VCH Verlag, 2011.

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Knopf, George K., and Amarjeet S. Bassi, eds. Smart Biosensor Technology. Second edition. | Boca Raton : Taylor & Francis, 2018.: CRC Press, 2018. http://dx.doi.org/10.1201/9780429429934.

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Usmani, Arthur M., and Naim Akmal, eds. Diagnostic Biosensor Polymers. Washington, DC: American Chemical Society, 1994. http://dx.doi.org/10.1021/bk-1994-0556.

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K, Knopf George, and Bassi Amarjeet S, eds. Smart biosensor technology. Boca Raton: CRC Press, 2007.

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Gabriele, Wagner, and Guilbault George G, eds. Food biosensor analysis. New York: M. Dekker, 1994.

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Biosensors: An introduction. Chichester: Wiley-Teubner, 1996.

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P, Buck Richard, and International Symposium on Biosensors: Fundamentals and Applications (1989 : University of North Carolina at Chapel Hill), eds. Biosensor technology: Fundamentals and applications. New York: M. Dekker, 1990.

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Mathewson, Paul R., and John W. Finley, eds. Biosensor Design and Application. Washington, DC: American Chemical Society, 1992. http://dx.doi.org/10.1021/bk-1992-0511.

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Book chapters on the topic "Biosensor"

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Lechuga, Laura M. "Biosensor." In Encyclopedia of Astrobiology, 311–15. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-44185-5_190.

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Lechuga, Laura M. "Biosensor." In Encyclopedia of Astrobiology, 200–204. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-11274-4_190.

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Betsy, C. Judith, and C. Siva. "Biosensor." In Fisheries Biotechnology and Bioinformatics, 153–59. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-6991-3_16.

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Zheng, Lei, and Ye Zhang. "Biosensor." In Clinical Molecular Diagnostics, 345–56. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1037-0_25.

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Lechuga, Laura M. "Biosensor." In Encyclopedia of Astrobiology, 1–6. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-27833-4_190-3.

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Lechuga, Laura M. "Biosensor." In Encyclopedia of Astrobiology, 402–6. Berlin, Heidelberg: Springer Berlin Heidelberg, 2023. http://dx.doi.org/10.1007/978-3-662-65093-6_190.

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Karube, Isao, and Izumi Kubo. "Micro-Biosensor." In Analytical Uses of Immobilized Biological Compounds for Detection, Medical and Industrial Uses, 207–18. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-2895-4_17.

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Baronas, Romas, Feliksas Ivanauskas, and Juozas Kulys. "Biosensor Action." In Springer Series on Chemical Sensors and Biosensors, 3–8. Dordrecht: Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-90-481-3243-0_1.

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Ohno, Yasuhide, Kenzo Maehashi, and Kazuhiko Matsumoto. "Graphene Biosensor." In Frontiers of Graphene and Carbon Nanotubes, 91–103. Tokyo: Springer Japan, 2015. http://dx.doi.org/10.1007/978-4-431-55372-4_7.

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Cardosi, M., and B. Haggett. "Biosensor devices." In Sensor Systems for Environmental Monitoring, 210–67. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-009-1571-8_7.

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Conference papers on the topic "Biosensor"

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Zhang, Bo, and Tony Zhengyu Cui. "Flexible Layer-by-Layer Self-Assembled Graphene Based Glucose Biosensors." In ASME 2011 International Mechanical Engineering Congress and Exposition. ASMEDC, 2011. http://dx.doi.org/10.1115/imece2011-64423.

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The manufacture and characterization of glucose biosensor based on layer by layer self assembled graphene are presented. Due to self assembly technique and flexible polymer substrate, the cost of the biosensor is very competitive. The resolution of the graphene based biosensor reaches down to 10 pM, which shows greater advantages over CNT based biosensor under the same conditions. The response time of graphene biosensor is less than 3 s, which is much faster than other materials and methods. This work demonstrates that graphene and polymers are very promising materials for the applications of low-cost glucose biosensors.
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Shah, Samar, Yaling Liu, and Walter Hu. "Characterization of Biosensor Detection Process at Ultra-Low Concentration Through a Stochastic Particle Model." In ASME 2010 First Global Congress on NanoEngineering for Medicine and Biology. ASMEDC, 2010. http://dx.doi.org/10.1115/nemb2010-13069.

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Biosensor detection process involves binding between biomolecules in a solution and a functionalized sensor surface. These sensors are time and cost efficient, sensitive, and enable new applications in medicine, drug design, and environmental monitoring. In literatures, various biosensor designs have been proposed, such as planar electrodes, nanowire, and nanospheres for different applications. However, to fully realize the potentials of these biosensors for biomarker/nanoparticle detection, several challenges must be addressed. In particular, ultra-sensitive biosensors are needed for detection of ultra-low concentration biomarkers such as cancer markers for early disease detection. The goal of this paper is to understand the diffusion process of biomarkers in a liquid solution and the binding with nanosensor surface through a stochastic particle model.
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Lall, Pradeep, Hyesoo Jang, Jinesh Narangaparambil, and Curtis Hill. "Development and Reliability Evaluation of Additively Printed Biosensing Device for Wearable Applications in Harsh Environment." In ASME 2023 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/ipack2023-111968.

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Abstract Using additive technologies for the production of printed circuit boards avoids the need for costly tooling, such as photomasks or etching containers for removing photoresist and metallization. Design and manufacturing based on software enables production flexibility, as well as speedier tool adjustments and design development. In addition, unlike traditional methods that remove unwanted material from a copper-clad board additive printing methods may be used to several fabrics, vehicles, and polymers with a variety of surfaces and forms. This allows for more flexibility and creativity in designing PCBs that can fit on different shapes and surfaces. This versatility to a broad variety of applications allows engineers to create diverse applications, such as wearable bio sensing device (biosensor) with an electrocardiography (ECG) sensor, an electrodermal activity (EDA) sensor, a pulse-oximetric sensor, a body temperature sensor, and a humidity sensor, and so on. devices that can measure and monitor various aspects of the human body’s health and status. The wearable biosensors can track parameters such as heart rate, blood oxygen level, skin conductance, body temperature, and humidity. This data can provide useful information and feedback for medical diagnosis, fitness tracking, or stress management. Due to its potential for adaptability and integration, the development of additively printed wearable biosensors has been the subject of several prior investigations. However, there are some challenges in terms of the reliability and durability of current wearable biosensor technology when flexing force is coupled with it. They need to withstand different environmental conditions and mechanical stresses that can affect their performance and quality. For the avoidance of stability issues, it is required to develop a better printing technique, process recipe, and sensing material encapsulation. In this research paper, the direct write (D-write) printing approach was employed with a nScrypt printer to print integrated wearable biosensor patch with the circuits, encapsulations, body temperature sensor, humidity sensor, pulse-oximetric (pulse-Ox) sensor and electrodermal activity (EDA) sensor on the integrated wearable biosensor. We also print electrically conductive adhesive (ECA) pads to attach the components such as a flexible battery, microcontroller, and wireless module. Additionally, we developed firmware and data acquisition software for the biosensor to collect and transmit the biosignals to mobile devices. We tested the biosensor under various conditions such as different temperatures, humidities, and body statuses (resting, walking, and running). We evaluated the accuracy, repeatability, stability, sensitivity, linearity, response time, and hysteresis effect of each sensor by comparing them with reference devices. The biosensor has been characterized by analyzing the biosignals with respect to the various conditions (temperature, humidity, and status of the human body). In addition, the assessment of the sensor accuracy and reliability in harsh conditions such as humidity and temperature fluctuation, has been measured. In conclusion, we have developed an integrated wearable biosensor using additive technologies for printed circuit boards. Our biosensor can monitor multiple vital signs of the human body with high reliability and flexibility. Our work contributes to advancing sustainable additive manufacturing of electronic devices for health care applications.
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Schulz, Mark J., Amos Doepke, Xuefei Guo, Julia Kuhlmann, Brian Halsall, William Heineman, Zhongyun Dong, et al. "Responsive Biosensors for Biodegradable Magnesium Implants." In ASME 2009 International Mechanical Engineering Congress and Exposition. ASMEDC, 2009. http://dx.doi.org/10.1115/imece2009-13101.

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A biosensor is an electronic device that measures biologically important parameters. An example is a sensor that measures the chemicals and materials released during corrosion of a biodegradable magnesium implant that impact surrounding cells, tissues and organs. A responsive biosensor is a biosensor that responds to its own measurements. An example is a sensor that measures the corrosion of an implant and automatically adjusts (slows down or speeds up) the corrosion rate. The University of Cincinnati, the University of Pittsburgh, North Carolina A&T State University, and the Hannover Medical Institute are collaborators in an NSF Engineering Research Center (ERC) for Revolutionizing Metallic Biomaterials (RBM). The center will use responsive sensors in experimental test beds to develop biodegradable magnesium implants. Our goal is to develop biodegradable implants that combine novel bioengineered materials based on magnesium alloys, miniature sensor devices that monitor and control the corrosion, and coatings that slow corrosion and release biological factors and drugs that will promote healing in surrounding tissues. Responsive biosensors will monitor what is happening at the interface between the implant and tissue to ensure that the implant is effective, biosafe, and provides appropriate strength while degrading. Corrosion behavior is a critical factor in the design of the implant. The corrosion behavior of implants will be studied using biosensors and through mathematical modeling. Design guidelines will be developed to predict the degradation rate of implants, and to predict and further study toxicity arising from corrosion products (i.e., Mg ion concentrations, pH levels, and hydrogen gas evolution). Knowing the corrosion rate will allow estimations to be made of implant strength and toxicity risk throughout the degradation process.
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Neizvestny, Igor G. "Nanowire biosensor." In 2008 9th International Workshop and Tutorials on Electron Devices and Materials. IEEE, 2008. http://dx.doi.org/10.1109/sibedm.2008.4585837.

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Lechuga, L. M., Mauricio Carbajal, Luis Manuel Montaño, Oscar Rosas-Ortiz, Sergio A. Tomas Velazquez, and Omar Miranda. "Biosensor Devices." In Advanced Summer School in Physics 2007. AIP, 2007. http://dx.doi.org/10.1063/1.2825120.

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Liu, Fei, Anis N. Nordin, Fang Li, and Ioana Voiculescu. "A Sensitive Multiparametric Biosensor With Capabilities of Rapid Toxicity Detection of Drinking Water." In ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-62281.

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Recently, there has been interest to develop biosensors based on live mammalian cells to monitor the toxicity of water. The cell viability after exposure to toxic water can be monitored by electric cell-substrate impedance sensing (ECIS) of the cell membrane. However, these impedance based toxicity sensors can only provide one single sensing endpoint (impedance measurement), and many toxicants cannot be detected at the concentration between Military Exposure Guideline levels and estimated Human Lethal Concentrations. The goal of this paper is to provide a rapid and sensitive sensing platform for long-term water toxicity detection. In this paper a novel multiparametric biosensor with integrated microfluidic channels for water toxicity detection is presented. Toxicity tests to study bovine aortic endothelial cells (BAECs) responsiveness to health-threatening concentrations of ammonia in de-ionized (DI) water will be presented. We demonstrated the BAECs can rapidly respond to ammonia concentrations between the military exposure guideline of 2mM and human lethal concentration of 55mM. The successful testing of water toxicity by simultaneous gravimetric and impedimetric measurements indicates that the multiparametric biosensor platform is able to perform rapid and sensitive detection of water toxicity and minimize the false-positive rate.
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Malima, Asanterabi, Ahmed Busnaina, and Sivasubramanian Somu. "Biosensor Microassembly Platform: Design and Automation." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-87618.

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We present a custom built Biosensor Microassembly Platform (BMP) for assembling a nanoparticles-based microscale in-vivo biosensor. Conducting directed assembly of nanoparticles on a 0.01 mm2 microchip is a very challenging problem. Complexities arise from assembling micro-components of different materials, and assembling antibody functionalized nanoparticles into their predetermined nanoscale trenches on the biosensor. Using our designed platform, we merge vision information with motion control efficiently, so that precise manipulation of the stages and microscopes facilitates the assembly process of the in-vivo biosensor. Along with Biosensor Microassembly Platform system design and automation, we demonstrate assembly of an in-vivo biosensor which has numerous applications in biomedical and health industry.
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Gunda, Naga Siva Kumar, and Sushanta K. Mitra. "Microfluidic Based Biosensor for Detection of Cardiac Markers." In ASME 2013 Fluids Engineering Division Summer Meeting. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/fedsm2013-16270.

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Myocardial Infarction (MI) occurs when the blood flow to the heart is blocked. It is major threat to human kind. Current laboratory and ELISA tests are expensive, time consuming, and are not very sensitive. Biosensors can play an important role in the diagnosis of MI without relying on hospital visits. Therefore, researchers are focusing to develop rapid, hand-held, inexpensive biosensors for detecting cardiac markers. In the present study, one of the cardiac markers (Troponin T) is detected using microfluidic based biosensor. Troponin T (cTnT) releases in to the blood serum within 4–6 h after minor heart attack and remains elevated for up to 2 weeks, which will help in diagnosing the heart condition. In this work, a microfluidic channel with an array of gold strips is considered for detecting and quantifying the Troponin T in an aqueous solution. Troponin T primary (capture) antibody is immobilized on gold strip using self assembled monolayer (SAM) consisting of a homogeneous mixture of oligo (ethylene glycol) (OEG)-terminated alkanethiolate and mercaptohexadecanoic acid (MHDA). Then, an aqueous solution containing Troponin T antigen is injected into the microchannel to facilitate antibody-antigen reaction to take place in less time. Later, FITC tagged Troponin T secondary (detection) antibody is dispensed in to the channel for quantification of Troponin T antigen. Using confocal fluorescent reader, the variation of fluorescent intensity across the microchannel is measured and quantified the concentration of Troponin T antigen with calibrated samples. Contact angle measurement system, Fourier Transform Infrared Spectroscopy and Ellipsometer are used to characterize the surface properties at each stage of biomolecule immobilization.
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Ducloux, Olivier, Elisabeth Galopin, Farzam Zoueshtiagh, Alain Merlen, and Vincent Thomy. "Surface Acoustic Wave-Induced Microstreaming in Droplets for the Enhancement of Biosensing Performances." In ASME 2010 8th International Conference on Nanochannels, Microchannels, and Minichannels collocated with 3rd Joint US-European Fluids Engineering Summer Meeting. ASMEDC, 2010. http://dx.doi.org/10.1115/fedsm-icnmm2010-30966.

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A droplet-based micro-total analysis system (microTAS) based on digital microfluidics, involving surface acoustic wave (SAW) microstreaming dedicated to the enhancement of the performance of biosensors was designed and studied. We first present the characterization of the flow induced in the droplet during SAW stirring. We then present the evaluation of the biosensor performance enhancement obtained using SAW, evaluated by finite element simulation. We finally stress on the importance of the Damko¨her and Peclet numbers in the design of stirring-based microTAS systems.
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Reports on the topic "Biosensor"

1

Kubicek-Sutherland, Jessica Zofie. Universal Bacterial Biosensor. Office of Scientific and Technical Information (OSTI), July 2017. http://dx.doi.org/10.2172/1369153.

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Thompson, Richard B. Fiber Optic Metal Ion Biosensor. Fort Belvoir, VA: Defense Technical Information Center, May 2002. http://dx.doi.org/10.21236/ada402530.

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Golden, Carole, Al Eckhardt, Eric Espenhahn, and Natasha Popovich. Portable Electrochemical DNA Biosensor Unit. Fort Belvoir, VA: Defense Technical Information Center, July 2002. http://dx.doi.org/10.21236/ada414610.

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Stice, Steven L., Jamie Chilton, and Allan Powe. Human Neural Cell-Based Biosensor. Fort Belvoir, VA: Defense Technical Information Center, June 2010. http://dx.doi.org/10.21236/ada522666.

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Stice, Steven L., and Jamie Chilton. Human Neural Cell-Based Biosensor. Fort Belvoir, VA: Defense Technical Information Center, October 2012. http://dx.doi.org/10.21236/ada566123.

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Stice, Steven L. Human Neural Cell-Based Biosensor. Fort Belvoir, VA: Defense Technical Information Center, December 2012. http://dx.doi.org/10.21236/ada571881.

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Stice, Steven L., and Jamie Chilton. Human Neural Cell-Based Biosensor. Fort Belvoir, VA: Defense Technical Information Center, May 2013. http://dx.doi.org/10.21236/ada585294.

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Stice, Steven L., Jamie Chilton, and Allan Powe. Human Neural Cell-Based Biosensor. Fort Belvoir, VA: Defense Technical Information Center, October 2011. http://dx.doi.org/10.21236/ada552021.

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Slice, Steven L., Jamie Chilton, and Allan Powe. Human Neural Cell-Based Biosensor. Fort Belvoir, VA: Defense Technical Information Center, January 2012. http://dx.doi.org/10.21236/ada554709.

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Stice, Steven L., and Jamie Chilton. Human Neural Cell-Based Biosensor. Fort Belvoir, VA: Defense Technical Information Center, April 2012. http://dx.doi.org/10.21236/ada559383.

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